This invention relates generally to the field of manufacturing, and more particularly to the field of tolerance control for manufactured parts.
Shape variation in manufactured parts is a normal occurrence. Parts are typically specified to have shapes that fall within predetermined dimensional limits. Dimensional control is important to downstream manufacturing operations because the success of some downstream manufacturing operations depends upon the as-manufactured shapes of the parts as they arrive to be processed. In a similar way, dimensional control is important to end users because it ensures the proper functionality of the part or final assembly. Furthermore, shape control is the key concept underlying the cost savings possible using interchangeable parts.
In many cases, tolerances are assigned to ensure that the shape of the part will be predictable or repeatable. It is not the exact shape of the part that drives the tolerance band, rather, it is the level of required repeatability. In general, the greater the required repeatability, the smaller the tolerance bands, and the more expensive the part. There is a cost savings opportunity where the cost of holding very tight tolerances has outstripped the savings of using fully interchangeable parts.
Thus there is a need for a method for controlling the variability of parts that does not rely solely on the control of manufacturing tolerances. With the convergence of flexible measuring technology in the form of Coordinate Measuring Machines (CMM""s), and computer controlled Numerical Control (NC) machining, we have an opportunity to develop techniques of manufacture that do not rely on fully interchangeable parts, and thereby do not require the expense of extremely tight tolerances. The inventors have accomplish this by substituting shape predictability for shape repeatability.
Accordingly, a method is disclosed herein for identifying shape variations in parts, the method comprising the steps of: obtaining measurements representing the shape of each of a plurality of parts; using the measurements to express the shape of each part as a respective function of a nominal part shape or as a function of a location in a part coordinate system, each function comprising a respective plurality of coefficients; and using the coefficients to define an error map for each respective part. Each respective function may be a discrete function or polynomial or trigonometric equation. The functions describing each of the plurality of parts can be combined to form a single function or set of functions describing the characteristics of the plurality. The method is further described as including the step of performing a principal component analysis across the error maps to identify the principal components of variation in the error maps. Once the principal components of variation are known, a plurality of sub-populations of the parts may be defined by identifying a plurality of ranges within at least one of the principal components of variation. Parts grouped into the various sub-populations may be treated differently for downstream processes. Furthermore, upstream processes may be controlled in order to affect the distribution of future parts within the various sub-populations.